Abstract:
Captopril, an anti-hypertensive drug, is seriously susceptible to oxidative degradation by high temperatures, humidity, and by the presence of hygroscopic excipients. Captopril disulphide is the main degradation product. In this study, multivariate control charts have been designed in order to monitor the captopril stability by using Hotelling's T2 statistics and the Squared Prediction Error (SPE). High-Performance Liquid Chromatography was the analytical technique used. The performance of T2 and SPE charts depend on the pre-processing applied. The scaling methods, particularly the chromatograms weighting in the region of captopril disulphide, highlight the relevant chemical information and sensitize the charts for the detection of minor changes in the operating conditions.
Fifty-two chromatograms from different batches of captopril in normal operating conditions were used for the preparation of T2 and SPE charts during the training stage. Eleven samples, seven within their shelf life and four after their expiration date were used in the validation stage. A stability study was performed by putting captopril samples in a 40 ± 2 °C and 75 ± 5% relative humidity climatic chamber. Captopril samples have been removed weekly from the climatic chamber over the course of six months. A Principal Components Analysis (PCA) was performed on the data set and the scores of the first 3 components were employed in the Hotelling's T2 building, while the SPE chart was designed with the model residuals. The multivariate control charts are sensitized to monitor chromatographic profile changes and captopril stability standard changes.
Highlights:
- The International Conference on Harmonisation (ICH) Q3 guidance currently recommends a pharmaceutical products definition change. The focus of the quality control changed from purity in active pharmaceutical ingredients (API) to impurity and degradation in finished pharmaceutical products. The need to develop and apply analytical chemistry and chemometrics techniques to monitor impurities is currently quite evident in the pharmaceutical industry.
- The Multivariate Statistical Process Control (MSPC) basis is collecting a historical data set when the process is working under normal operating conditions (NOC), performing a principal component analysis with historical data for modelling and extracting the correlation structure of several correlated variables and using the modelled information in the multivariate control chart design.
- Pre-processing of the chromatograms was required such as alignment of the retention times using algorithms such as Correlation Optimised Warping, removal of regions on the chromatograms that are not of interest and mean square root scaling to increase the sensitivity of multivariate analysis charts to detect small impurity peaks.
- The sensitivity for change detection of chromatographic profiles depended on the representativeness of the historic data (NOC), the pre-processing methods and on the number of principal components included in the NOC model, which was determined by minimizing the amount of type 1 errors of T2 during the training phase, when only NOC samples were used.
- The weighting of chromatograms in the region of captopril disulphide sensitized control charts for the detection of minor variations in impurity peaks.
- The validation stage with NOC samples allowed for the tuning of the sensitivity by weight adjusting until the minimization of type 1 and 2 errors.
- The SPE statistics were more sensitive to small variations in the impurity peaks.
- When applied to the stability set, the sample control output could be associated with changes in the chromatographic profile due to the increase of captopril disulphide content.
- Systematic variations of the T2 chart monitored signal also indicated a control output.
Citation:
Tôrres, A. R., Junior, S. G., & Fragoso, W. D., “Multivariate control charts for monitoring captopril stability”, Microchemical Journal, (2015), 118, 259-265.